In an experiment to determine the factors affecting tensile strength in steel plates, the tensilestrength (in kg/mm?), the manganese content (in parts per thousand), and the thickness (inmm) were measured for a sample of 20 plates. The following MINITAB output presents theresults of fitting the model Tensile strength = Bo + B1 Manganese + B2 Thickness.The regression equation isStrength = 26.641 + 3.3201 Manganese – 0.4249 ThicknessPredictorCoef StDevтConstant26.6412.723409.78 0.000Manganese 3.32010.33198 10.00 0.000Thickness -0.42490.12606 -3.37 0.004S = 0.8228 R-Sq = 86.2% R-Sq(adj) =84.6%Analysis of VarianceSourceDFMSRegressionResidual Error 1711.508 0.67692 72.0136.00553.190.000Total1983.517 Find a 95% confidence interval for the coefficient of Manganese.b.a.Find a 99% confidence interval for the coefficient of Thickness.Can you conclude that B1 > 3? Perform the appropriate hypothesis test.d.Can you conclude that B2 < -0.1? Perform the appropriate hypothesis test.C.

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A Bivariate Regression was conducted to evaluate the predictive relationship between total years of schooling and annual income. The results of the regression model were F(1,88) = 4.1, p < .05. What can be concluded about these results? Group of answer choices total years of schooling is a significant predictor of annual income. total years of schooling is not a significant predictor of annual income.
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A linear regression model based on a random sample of 36 observations on the response variable and 4 predictors has a multiple coefficient of determination equal to 0.697. What is the value of the adjusted multiple coefficient of determination?
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Let's study the relationship between brand, camera resolution, and internal storage capacity on the price of smartphones. Use α = .05 to perform a regression analysis of the Smartphones01CS dataset, and then answer the following questions. When you copy and paste output from MegaStat to answer a question, remember to choose to "Keep Formatting" to paste the text. a. Did you find any evidence of multicollinearity and variance inflation among the predictors. Explain your answer using a VIF analysis. b. Copy and paste the normal probability plot for your analysis. Is there any evidence that the errors are not normally distributed? Explain. c. Copy and paste the Residuals vs. Predicted Y-values. Does the pattern support the null hypothesis of constant variance for the errors? Explain. d. Study the residuals analysis. Which observations, if any, have unusual residuals? e. Study the residuals analysis. Calculate the leverage statistic. Which observations, if any, are high leverage…

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